Facilitating photo sharing

ABSTRACT

Embodiments generally relate to facilitating photo sharing among users of a social network system. In one embodiment, a method includes recognizing one or more people in a photo captured by a user. The method also includes sending a copy of the photo to at least one person recognized in the photo. The method also includes receiving, from the at least one person recognized in the photo, an indication of whether the at least one person approves the photo.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 13/602,134, filed on Sep. 1, 2012, of which is herebyincorporated by reference in its entirety.

TECHNICAL FIELD

Embodiments relate generally to social network systems, and moreparticularly to facilitating photo sharing.

BACKGROUND

When people in a group want to take a group photo, different individualsin the group often want to take a group photo with their own personalcameras so that different individuals each have a copy of the groupphoto. Furthermore, after a photo is taken, some individuals in thegroup may want to see the photo to make sure that they like how theylook in the photo. This requires a camera to be passed around so thatindividuals may approve the photo. Passing around a camera may disruptthe pose and formation of the people in the group. If the photo needs tobe retaken, the group needs to reassemble for another photo.

SUMMARY

Embodiments generally relate to facilitating photo sharing among usersof a social network system. In one embodiment, a method includesrecognizing one or more people in a photo captured by a user. The methodalso includes sending a copy of the photo to at least one personrecognized in the photo. The method also includes receiving, from the atleast one person recognized in the photo, an indication of whether theat least one person approves the photo.

With further regard to the method, the recognizing is based at least inpart on social connections. In one embodiment, the recognizing includesidentifying one or more faces of the one or more people in the photo,and matching the one or more identified faces to respective faces ofpeople who are socially connected to the user in a social networksystem. In one embodiment, the recognizing includes identifying at leastone face, and applying a facial recognition algorithm to the at leastone face. In one embodiment, the sending of the copy includesdetermining a device associated with the at least one person recognizedin the photo, and sending the copy of the photo to the device. In oneembodiment, the method also includes sending the indication to the user.In one embodiment, the method also includes sending to the user a promptto capture a new photo in response to an indication that the at leastone person disapproves the photo. In one embodiment, the method alsoincludes enabling the user to associate identifying labels withunmatched faces. In one embodiment, the method also includes enablingthe user to associate identifying labels with unrecognized faces byselecting people from a list of social connections in a social network.In one embodiment, the method also includes enabling the user to verifythe correctness of people recognized in the photo.

In another embodiment, a method includes recognizing one or more peoplein a photo captured by a user, where the recognizing is based at leastin part on social connections. The method also includes enabling theuser to associate identifying labels with unrecognized faces byselecting people from a list of social connections in a social network,and sending a copy of the photo to at least one person recognized in thephoto, where the sending of the copy includes determining a deviceassociated with the at least one person recognized in the photo, andsending the copy of the photo to the device. The method also includesreceiving, from the at least one person recognized in the photo, anindication of whether the at least one person approves the photo. Inresponse to an indication that the at least one person disapproves thephoto, the method also includes sending to the user a prompt to capturea new photo.

In another embodiment, a system includes one or more processors, andlogic encoded in one or more tangible media for execution by the one ormore processors. When executed, the logic is operable to performoperations including: recognizing one or more people in a photo capturedby a user; sending a copy of the photo to at least one person recognizedin the photo; and receiving, from the at least one person recognized inthe photo, an indication of whether the at least one person approves thephoto.

With further regard to the system, the recognizing is based at least inpart on social connections. In one embodiment, the logic when executedis further operable to perform operations including identifying one ormore faces of the one or more people in the photo, and matching the oneor more identified faces to respective faces of people who are sociallyconnected to the user in a social network system. In one embodiment, thelogic when executed is further operable to perform operations includingidentifying at least one face, and applying a facial recognitionalgorithm to the at least one face. In one embodiment, the logic whenexecuted is further operable to perform operations including determininga device associated with the at least one person recognized in thephoto, and sending the copy of the photo to the device. In oneembodiment, the logic when executed is further operable to performoperations including sending the indication to the user. In oneembodiment, the logic when executed is further operable to performoperations including sending to the user a prompt to capture a new photoin response to an indication that the at least one person disapprovesthe photo. In one embodiment, the logic when executed is furtheroperable to perform operations including enabling the user to associateidentifying labels with unmatched faces. In one embodiment, the logicwhen executed is further operable to perform operations includingenabling the user to associate identifying labels with unrecognizedfaces by selecting people from a list of social connections in a socialnetwork. In one embodiment, the logic when executed is further operableto perform operations including enabling the user to verify thecorrectness of people recognized in the photo.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of an example network environment,which may be used to implement the embodiments described herein.

FIG. 2 illustrates an example simplified flow diagram for facilitatingphoto sharing among users of a social network system.

FIG. 3 illustrates a block diagram of an example server device, whichmay be used to implement the embodiments described herein.

DETAILED DESCRIPTION

Embodiments described herein relate to photo sharing among users of asocial network system. In some embodiments, when a user of a cameradevice captures a photo of one or more people, a system recognizes oneor more of the people in the photo. In some embodiments, the systemrecognizes people in the photo based at least in part on socialconnections between the people in the photo and the user who capturedthe photo. For example, the system may identify one or more faces of oneor more people in the photo. The system may then match the identifiedfaces to respective faces of people who are socially connected to theuser in a social network system. In some embodiments, the system mayenable the user to verify the correctness of people recognized in thephoto. In some embodiments, the system may enable the user to associateidentifying labels with unrecognized faces by selecting people from alist of social connections on the social network.

The system then shares the photo of one or more people in the photo bysending a copy of the photo to the one or more people recognized in thephoto. In some embodiments, the sending of the copy may include thesystem determining a device such as a mobile phone associated with atleast one person recognized in the photo, and then sending the copy ofthe photo to the device of the recognized person. The system thenreceives from the person recognized in the photo, an indication ofwhether the recognized person approves the photo. The system then sendsthe indication to the user who captured the photo. In response to anindication that the recognized person disapproves the photo, the systemmay then send to the user who captured the photo a prompt to capture anew photo.

FIG. 1 illustrates a block diagram of an example network environment100, which may be used to implement the embodiments described herein. Inone embodiment, network environment 100 includes a system 102, whichincludes a server device 104 and a social network database 106. The termsystem 102 and phrase “social network system” may be usedinterchangeably. Network environment 100 also includes client devices110, 120, 130, and 140, which may communicate with each other via system102 and a network 150.

For ease of illustration, FIG. 1 shows one block for each of system 102,server device 104, and social network database 106, and shows fourblocks for client devices 110, 120, 130, and 140. Blocks 102, 104, and106 may represent multiple systems, server devices, and social networkdatabases. Also, there may be any number of client devices. In otherembodiments, network environment 100 may not have all of the componentsshown and/or may have other elements including other types of elementsinstead of, or in addition to, those shown herein.

In various embodiments, users U1, U2, U3, and U4 may take photos as wellas receive photos for viewing and/or approval using respective clientdevices 110, 120, 130, and 140. Various hardware and software componentsused to implement embodiments described herein may reside on clientdevices 110, 120, 130, and 140, and client devices 110, 120, 130, and140 may be any combination of smartphones, tablets, notebook computers,or any other suitable devices that include an Internet-connected camera.

As described in various embodiments herein, users U1, U2, U3, and U4 mayrepresent members/individuals of a group participating in a group photo.In some embodiments, each individual in a group photo may participate inphoto sharing and may be registered to a photo sharing service/socialnetwork. Each individual may also be socially connected to a given usertaking one or more photos (e.g., the photographer) on the social networksystem.

FIG. 2 illustrates an example simplified flow diagram for facilitatingphoto sharing among users of a social network system. Referring to bothFIGS. 1 and 2, a method is initiated in block 202, where system 102receives a photo with one or more people in a photo captured by a user.In various embodiments, the user may capture the photo using anysuitable device such as a camera, smartphone, tablet, etc. In variousembodiments, such a device is capable of connecting to the Internetafter taking the photo. System 102 may receive the photo being uploaded(e.g., to the social network photo sharing service), and then mayrecognize the individuals in the photo.

In block 204, system 102 recognizes one or more people in a photocaptured by a user. As described in more detail below, system 102 mayapply a facial recognition algorithm to recognize the people in thephoto. In various embodiments, system 102 enables users of the socialnetwork system to specify and/or consent to the use of personalinformation, which may include system 102 using their faces in photos orusing their identity information in recognizing people identified inphotos. For example, system 102 may provide users with multipleselections directed to specifying and/or consenting to the use ofpersonal information. For example, selections with regard to specifyingand/or consenting may be associated with individual photos, all photos,individual photo albums, all photo albums, etc. The selections may beimplemented in a variety of ways. For example, system 102 may causebuttons or check boxes to be displayed next to various selections. Inone embodiment, system 102 enables users of the social network tospecify and/or consent to the use of using their photos for facialrecognition in general. Example embodiments for recognizing faces andother objects are described in more detail below.

In some embodiments, the recognizing of people is based at least in parton social connections. For example, in some embodiments, system 102 mayidentify one or more faces of the one or more people in the photo.System 102 may then match the one or more identified faces to respectivefaces of people who are socially connected to the user in a socialnetwork system. In some embodiments, system 102 may match one or moreidentified faces to respective faces of people who are sociallyconnected to one or more people already recognized in the photo.Matching faces of people based on social connection avoids system 102needing to do a global match against everyone in the social network. Insome embodiments, system 102 may, if needed, still perform a globalmatch against people in the social network who are not sociallyconnected to the user who captured the photo or connected to the peoplerecognized in the photo.

In some embodiments, for faces which cannot be matched, the user whocaptured the photo may manually select the individuals from a list offriends on the social network system. For example, in some embodiments,system 102 may display a list of socially connected people (e.g.,friends) identified in the photo. System 102 may then enable the user toverify the correctness of people recognized in the photo. This alsoallows the photo to be automatically tagged, which reduces the amount ofmanual work for the user who captured the photo. System 102 may alsoenable the user to edit any tags if needed. In some embodiments, system102 enables the user to associate identifying labels with unrecognizedfaces by selecting people from a list of social connections in a socialnetwork. In some embodiments, system 102 enables the user who capturedthe photo as well as recipients of copies of the photo to associateidentifying labels with unrecognized faces by selecting people fromtheir lists of social connections in a social network. In someembodiments, a given user who associates an identifying label with anunrecognized face may be prompted to enter contact information (e.g.,phone number, email address, etc.) in order to send a copy of the phototo that person. System 102 may then use the contact information to sendsubsequent photos to that person.

In some embodiments, system 102 may determine that one or more peopleidentified in a given photo are not a part of the group. For example, astranger may be captured in the background, and system 102 may determinethat the stranger appears to be too far away (e.g., based on therelative size of the face) and/or looking in a different direction fromthe rest of the people in the group to be a part of the group. In someembodiments, system 102 may ignore the face during the recognitionprocess or may prompt to the user who captured the photo to verifywhether the person in question is a part of the group. In someembodiments, system 102 may not recognize the person in question, andthe user would not manually associate an identifying label with thestranger. As such, system 102 may ignore the stranger during therecognition process of subsequent photos.

In block 206, system 102 sends a copy of the photo to one or more peoplerecognized in the photo. In various embodiments, system 102 immediatelysends a copy of the photo to the people in the photo, which enables thepeople recognized in the photo to seamlessly receive a copy of the phototo keep and/or to approve. As such, individuals in the photo might nothave the desire to take another photo with their own personal camera,which may be unnecessary.

In some embodiments, system 102 may utilize an online registry serviceto automatically make the photo available to each person in the photo.If a given individual in the photo has a smartphone (or any othersuitable device for receiving and view photos), that individual maynearly instantaneously view the photo. In some embodiments, in ordersend a copy of the photo to a given person recognized in the photo,system 102 may determine or locate a device associated with the givenperson recognized in the photo, and then send the copy of the photo tothat device. In some embodiments, system 102 may utilize user profileinformation such as a phone number, email address, media access control(MAC) address, etc. associated with a given person recognized in thephoto in order to send the photo to a device associated with that givenperson.

The recipients of the photo may then approve or disapprove the photo.This also enables the people in the photo to approve the image and sharethe image with their friends. In some embodiments, system 102 may sendout a notification (which may be turned “on” by default) such that thedevice of each person who receives a copy will alert them that the photohas been shared with them to illicit their approval or disapproval ofthe photo. If one or more people disapprove the photo, another photo canbe taken immediately before the people go “out of formation.” System 102may provide each person with one or more selections to approve ordisapprove the photo.

In some embodiments, system 102 may prompt the user capturing the photowhether or not to share the photo with the group. Also, if the usertakes the photo with him or herself in the photo (e.g., using a timer orhaving a stranger take the picture, etc.), system 102 may enable thatuser (e.g., owner of the camera device) to approve or disapprove thephoto before anyone else looks at it.

In block 208, system 102 receives, from the at least one personrecognized in the photo, an indication of whether the at least oneperson in the photo approves or disapproves the photo. In response to anindication that the at least one person disapproves the photo, in someembodiments, system 102 sends a prompt to the user to capture a newphoto. Embodiments described herein render such passing around of acamera for different individuals to view and approve or disapproveunnecessary, as each individual would have already received a copy ofthe photo on their own devices (e.g., camera, smartphone, tablet, etc.).

In some embodiments, system 102 may apply various policies with regardto a given photo. For example, in some embodiments, if a persondisapproves a given photo, system 102 may automatically prompt the userwho captured the photo to take another photo. In some embodiments, aperson who disapproves a photo may still keep the photo even thoughanother photo may be taken. In some embodiments, a disapproval of aphoto may cause system 102 to prevent the other people in the photo tokeep a copy of the disapproved photo, or may otherwise delete the photo.Various policies are possible, depending on the particularimplementations.

Although the steps, operations, or computations may be presented in aspecific order, the order may be changed in particular embodiments.Other orderings of the steps are possible, depending on the particularimplementation. In some particular embodiments, multiple steps shown assequential in this specification may be performed at the same time.

While system 102 is described as performing the steps as described inthe embodiments herein, any suitable component or combination ofcomponents of system 102 or any suitable processor or processorsassociated with system 102 may perform the steps described.

In various embodiments, system 102 may utilize a variety of recognitionalgorithms to recognize faces in photos. Such facial algorithms may beintegral to system 102. System 102 may also access recognitionalgorithms provided by software that is external to system 102 and thatsystem 102 accesses.

In various embodiments, system 102 obtains reference images of users ofthe social network system, where each reference image includes an imageof a face that is associated with a known user. The user is known, inthat system 102 has the user's identity information such as the user'sname and other profile information. In one embodiment, a reference imagemay be, for example, a profile image that the user has uploaded. In oneembodiment, a reference image may be based on a composite of a group ofreference images.

In one embodiment, to recognize a face in a photo, system 102 maycompare the face (i.e., image of the face) and match the face toreference images of users of the social network system. Note that theterm “face” and the phrase “image of the face” are used interchangeably.For ease of illustration, the recognition of one face is described insome of the example embodiments described herein. These embodiments mayalso apply to each face of multiple faces to be recognized.

In one embodiment, system 102 may search reference images in order toidentify any one or more reference images that are similar to the facein the photo.

In one embodiment, for a given reference image, system 102 may extractfeatures from the image of the face in a photo for analysis, and thencompare those features to those of one or more reference images. Forexample, system 102 may analyze the relative position, size, and/orshape of facial features such as eyes, nose, cheekbones, mouth, jaw,etc. In one embodiment, system 102 may use data gathered from theanalysis to match the face in the photo to one more reference imageswith matching or similar features. In one embodiment, system 102 maynormalize multiple reference images, and compress face data from thoseimages into a composite representation having information (e.g., facialfeature data), and then compare the face in the photo to the compositerepresentation for facial recognition.

In some scenarios, the face in the photo may be similar to multiplereference images associated with the same user. As such, there would bea high probability that the person associated with the face in the photois the same person associated with the reference images.

In some scenarios, the face in the photo may be similar to multiplereference images associated with different users. As such, there wouldbe a moderately high yet decreased probability that the person in thephoto matches any given person associated with the reference images. Tohandle such a situation, system 102 may use various types of facialrecognition algorithms to narrow the possibilities, ideally down to onebest candidate.

For example, in one embodiment, to facilitate in facial recognition,system 102 may use geometric facial recognition algorithms, which arebased on feature discrimination. System 102 may also use photometricalgorithms, which are based on a statistical approach that distills afacial feature into values for comparison. A combination of thegeometric and photometric approaches could also be used when comparingthe face in the photo to one or more references.

Other facial recognition algorithms may be used. For example, system 102may use facial recognition algorithms that use one or more of principalcomponent analysis, linear discriminate analysis, elastic bunch graphmatching, hidden Markov models, and dynamic link matching. It will beappreciated that system 102 may use other known or later developedfacial recognition algorithms, techniques, and/or systems.

In one embodiment, system 102 may generate an output indicating alikelihood (or probability) that the face in the photo matches a givenreference image. In one embodiment, the output may be represented as ametric (or numerical value) such as a percentage associated with theconfidence that the face in the photo matches a given reference image.For example, a value of 1.0 may represent 100% confidence of a match.This could occur, for example, when compared images are identical ornearly identical. The value could be lower, for example 0.5 when thereis a 50% chance of a match. Other types of outputs are possible. Forexample, in one embodiment, the output may be a confidence score formatching.

Embodiments described herein provide various benefits. For example,embodiments enable users to immediate share photos with individuals inthe photos. Individuals in the photos may quickly and convenientlyreceive copies of photos for approval or disapproval.

FIG. 3 illustrates a block diagram of an example server device 300,which may be used to implement the embodiments described herein. Forexample, server device 300 may be used to implement server device 104 ofFIG. 1, as well as to perform the method embodiments described herein.In one embodiment, server device 300 includes a processor 302, anoperating system 304, a memory 306, and an input/output (I/O) interface308. Server device 300 also includes a social network engine 310 and amedia application 312, which may be stored in memory 306 or on any othersuitable storage location or computer-readable medium. Media application312 provides instructions that enable processor 302 to perform thefunctions described herein and other functions.

For ease of illustration, FIG. 3 shows one block for each of processor302, operating system 304, memory 306, I/O interface 308, social networkengine 310, and media application 312. These blocks 302, 304, 306, 308,310, and 312 may represent multiple processors, operating systems,memories, I/O interfaces, social network engines, and mediaapplications. In other embodiments, server device 300 may not have allof the components shown and/or may have other elements including othertypes of elements instead of, or in addition to, those shown herein.

Although the description has been described with respect to particularembodiments thereof, these particular embodiments are merelyillustrative, and not restrictive. Concepts illustrated in the examplesmay be applied to other examples and embodiments.

Note that the functional blocks, methods, devices, and systems describedin the present disclosure may be integrated or divided into differentcombinations of systems, devices, and functional blocks as would beknown to those skilled in the art.

Any suitable programming languages and programming techniques may beused to implement the routines of particular embodiments. Differentprogramming techniques may be employed such as procedural orobject-oriented. The routines may execute on a single processing deviceor multiple processors. Although the steps, operations, or computationsmay be presented in a specific order, the order may be changed indifferent particular embodiments. In some particular embodiments,multiple steps shown as sequential in this specification may beperformed at the same time.

A “processor” includes any suitable hardware and/or software system,mechanism or component that processes data, signals or otherinformation. A processor may include a system with a general-purposecentral processing unit, multiple processing units, dedicated circuitryfor achieving functionality, or other systems. Processing need not belimited to a geographic location, or have temporal limitations. Forexample, a processor may perform its functions in “real-time,”“offline,” in a “batch mode,” etc. Portions of processing may beperformed at different times and at different locations, by different(or the same) processing systems. A computer may be any processor incommunication with a memory. The memory may be any suitableprocessor-readable storage medium, such as random-access memory (RAM),read-only memory (ROM), magnetic or optical disk, or other tangiblemedia suitable for storing instructions for execution by the processor.

What is claimed is:
 1. A computer-implemented method, the methodcomprising: recognizing one or more people from one or more faces in aphoto including two or more faces captured by a user; sending a copy ofthe photo in real-time to at least one person's device recognized in thephoto; and in response to an indication that the at least one persondisapproves the photo, sending to the user a prompt to capture a newphoto, wherein the at least one person who disapproves the photo isdifferent from the user who captured the photo.
 2. The method of claim1, wherein the recognizing is based at least in part on socialconnections.
 3. The method of claim 1, wherein the recognizingcomprises: identifying one or more faces of the one or more people inthe photo; and matching the one or more identified faces to respectivefaces of people who are socially connected to the user in a socialnetwork system.
 4. The method of claim 1, wherein the recognizingcomprises: identifying one or more faces of the one or more people inthe photo; and applying a facial recognition algorithm to the one ormore faces.
 5. The method of claim 1, wherein the recognizing comprises:identifying the one or more faces of the one or more people in thephoto; and applying a facial recognition algorithm to the one or morefaces, wherein the facial recognition algorithm matches the one or moreidentified faces to respective faces of people who are sociallyconnected to the user in a social network system.
 6. The method of claim1, wherein the sending of the copy comprises: determining a deviceassociated with the at least one person recognized in the photo; andsending the copy of the photo to the device.
 7. The method of claim 1,further comprising sending the indication to the user.
 8. The method ofclaim 1, further comprising receiving, from the at least one personrecognized in the photo, an indication of whether the at least oneperson approves the photo.
 9. The method of claim 1, further comprisingsending to the user a prompt to capture a new photo in response to anindication that the at least one person disapproves the photo.
 10. Themethod of claim 1, further comprising enabling the user to associateidentifying labels with unmatched faces.
 11. The method of claim 1,further comprising enabling the user to associate identifying labelswith unrecognized faces by selecting people from a list of socialconnections in a social network.
 12. The method of claim 1, furthercomprising enabling the user to verify the correctness of peoplerecognized in the photo.
 13. A system comprising: one or moreprocessors; and logic encoded in one or more memory devices forexecution by the one or more processors and when executed operable toperform operations comprising: recognizing one or more people from oneor more faces in a photo including two or more faces captured by a user;sending a copy of the photo in real-time to at least one person's devicerecognized in the photo; and in response to an indication that the atleast one person disapproves the photo, sending to the user a prompt tocapture a new photo, wherein the at least one person who disapproves thephoto is different from the user who captured the photo.
 14. The systemof claim 13, wherein the recognizing is based at least in part on socialconnections.
 15. The system of claim 13, wherein the logic when executedis further operable to perform operations comprising: identifying one ormore faces of the one or more people in the photo; and matching the oneor more identified faces to respective faces of people who are sociallyconnected to the user in a social network system.
 16. The system ofclaim 13, wherein the logic when executed is further operable to performoperations comprising: identifying one or more faces of the one or morepeople in the photo; and applying a facial recognition algorithm to theone or more faces.
 17. The system of claim 13, wherein the recognizingcomprises: identifying the one or more faces of the one or more peoplein the photo; and applying a facial recognition algorithm to the one ormore faces, wherein the facial recognition algorithm matches the one ormore identified faces to respective faces of people who are sociallyconnected to the user in a social network system.
 18. The system ofclaim 13, wherein the logic when executed is further operable to performoperations comprising: determining a device associated with the at leastone person recognized in the photo; and sending the copy of the photo tothe device.
 19. The system of claim 13, wherein the logic when executedis further operable to perform operations comprising sending theindication to the user.
 20. A system comprising: a storage device; andone or more processors accessing the storage device and operable toperform operations comprising: recognizing one or more people from oneor more faces in a photo including two or more faces captured by a user;sending a copy of the photo in real-time to at least one person's devicerecognized in the photo; and in response to an indication that the atleast one person disapproves the photo, sending to the user a prompt tocapture a new photo, wherein the at least one person who disapproves thephoto is different from the user who captured the photo.